Moghadas, SeyedTariq, Mehreen2021-11-152021-11-1520212021-11-15http://hdl.handle.net/10315/38640Many countries implemented strict social distancing measures to reduce infections, hospitalizations, and deaths during the coronavirus disease 2019 (COVID-19) pandemic. We developed an age-structured deterministic compartmental model and parameterized it with recent COVID-19 estimates to evaluate the effect of self-isolation and stay-at-home orders on infections, hospitalizations, and deaths. The findings show that a 5-month stay-at-home order targeting older individuals ($\geq 50$ years) had the greatest reduction in hospitalizations (over $47\%$) and deaths (over $55\%$). A 5-month stay-at-home order for individuals $\geq 65$ years had the most hospitalizations (over 0.0087) and deaths (0.0027) averted per-person practising the stay-at-home order. School closures reduced the outcomes of interest if implemented for a longer duration. Due to the increase in infections post-lockdown (shown in scenario 2), the strategies tested in this study can be used to strategically lift lockdown orders and minimize the burden on healthcare systems until herd immunity is achieved (through vaccination).Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.Public policyElectronic Thesis or Dissertation2021-11-15stay-at-home ordersdisease modellingCOVID-19 pandemicmathematical modelling